This post is part of a series that interviews some notable bioinformaticians to get their views on various aspects of bioinformatics research. Hopefully these answers will prove useful to others in the field, especially to those who are just starting their bioinformatics careers.

This is the third 'binary' post in this series — where the interviewee number consists of just ones and/or zeros. If this fact makes you excited, then you probably need to get out more.

Lex Nederbragt works as a Bioinformatician at the Norwegian Sequencing Centre (where they probably do more than just sequence Norwegians). He is also an Associate Professor at the Centre for Ecological and Evolutionary Synthesis (CEES), University of Oslo.

As a Dutchman living in the least populous of the three Scandinavian Kingdoms, Lex can take comfort in knowing that the Netherlands retain the upper hand in their battles with Norway on the football field.

Away from football — and this is the last chance you'll have to get away from football for the next few weeks — Lex is someone who posts fantastic amounts of useful information on his blog. If you have any interest in high-throughput sequencing and assembly, then you owe it to yourself to follow his blog updates.

You can find out more about Lex by following him on twitter (@lexnederbragt), or reading his aforementioned blog (In between lines of code) or his other blog…presumably the world's only blog devoted to the Newbler assembler.

And so on to the 101 questions...

001. What's something that you enjoy about current bioinformatics research?

The increasing focus on reproducibility and reusability. Making sure others can reproduce your work is such a fundamental aspect of science, and computational work should be easy to reproduce in principle. It is fascinating to see how difficult this turns out to be in practice — even in cases where the description of the work is very complete.

010. What's something that you *don't* enjoy about current bioinformatics research?

I'm not the first one to complain about the seemingly unlimited growth in tools meant for the same job, e.g., short read mappers. My field of interest is de novo genome assembly, and there too new tools appear regularly. I think it is about time we settle on a set of tools that appear to be best suited for the job, and move on to finding ways to determine which tools works best for each individual dataset and research question. In the case of assembly, we basically already know the set of programs that generally perform well. Now we need to develop and implement evaluation tools that tell a researcher which assembly of the data is the best one for their purposes.

011. If you could go back in time and visit yourself as an 18 year old, what single piece of advice would you give yourself to help your future bioinformatics career?

I am a bit ambivalent here. It took me a long time to realize that I wanted to become a bioinformatician, I missed a lot of signals how much I enjoyed programming, for example. So, I would like to tell myself to explore computational science much more than I did. On the other hand, waiting this long to make the switch to bioinformatics meant I have acquired a very firm background in biology. I find this essential for my work, as it allows me to make connections between the technological aspects of high-throughput sequencing experiments and data analysis, and the biological questions that inspired the experiments in the first place. So, I would also like to tell myself to keep on studying biology.

100. What's your all-time favorite piece of bioinformatics software, and why?

The Newbler assembly and mapping program from Roche/454 Life Sciences. It is not the program per se (it's good, but not necessarily the best; nor is it open source, for that matter). However, it is through the use of this program I was propelled into bioinformatics. I became very familiar with it and started scripting to massage its output. I even wrote a user-oriented manual for Newbler. These days, I use many more assembly programs besides Newbler, but my bioinformatics 'roots' will always be Newbler.

101. IUPAC describes a set of 18 single-character nucleotide codes that can represent a DNA base: which one best reflects your personality?

B, as it stands for 'C or G or T', so it is flexible, allowing several alternatives and keeping options open. But it also means knowing your limits, not everything goes. I also like to have a 'plan B' in the back of my head.